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Activity scheduling and resource allocation with uncertainties and learning in activities

Felix T.S. Chan (Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong)
Zhengxu Wang (Department of Business Administration, Dongbei University of Finance and Economics, Dalian, China)
Yashveer Singh (Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India)
X.P. Wang (Institute of Systems Engineering, Dalian University of Technology, Dalian, China)
J.H. Ruan (College of Economics and Management, Northwest Agriculture and Forestry University, Yangling, China)
M.K. Tiwari (Department of Industrial and Systems Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 8 July 2019

Abstract

Purpose

The purpose of this paper is to develop a model which schedules activities and allocates resources in a resource constrained project management problem. This paper also considers learning rate and uncertainties in the activity durations.

Design/methodology/approach

An activity schedule with requirements of different resource units is used to calculate the objectives: makespan and resource efficiency. A comparisons between non-dominated sorting genetic algorithm – II (NSGA-II) and non-dominated sorting genetic algorithm – III (NSGA-III) is done to calculate near optimal solutions. Buffers are introduced in the activity schedule to take uncertainty into account and learning rate is used to incorporate the learning effect.

Findings

The results show that NSGA-III gives better near optimal solutions than NSGA-II for multi-objective problem with different complexities of activity schedule.

Research limitations/implications

The paper does not considers activity sequencing with multiple activity relations (for instance partial overlapping among different activities) and dynamic events occurring in between or during activities.

Practical implications

The paper helps project managers in manufacturing industry to schedule the activities and allocate resources for a near-real world environment.

Originality/value

This paper takes into account both the learning rate and the uncertainties in the activity duration for a resource constrained project management problem. The uncertainty in both the individual durations of activities and the whole project duration time is taken into consideration. Genetic algorithms were used to solve the problem at hand.

Keywords

Acknowledgements

The work described in this paper was supported by grant from The Natural Science Foundation of China (Grant No. 71471158), China Postdoctoral Science Foundation funded project (Grant No. 2018M631792) and The Department of Education of Liaoning Province (Grant No. LN2017QN006).

Citation

Chan, F.T.S., Wang, Z., Singh, Y., Wang, X.P., Ruan, J.H. and Tiwari, M.K. (2019), "Activity scheduling and resource allocation with uncertainties and learning in activities", Industrial Management & Data Systems, Vol. 119 No. 6, pp. 1289-1320. https://doi.org/10.1108/IMDS-01-2019-0002

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited